Machine-learning could tackle antibiotic-resistant bacteria

A team of researchers is using a potent machine-learning system to study an infection that’s highly resistant to antibiotic therapies. With the work already yielding positive results, it could lead to improved understanding of bacterium, and ultimately the discovery of new treatments. A recently-developed algorithm known as a denoising autoencoder was originally designed to pick out prominent patterns or features in large sets of data, without first being told specifically what to look for. The technique has been used for various purposes in the past, including analyzing random collections of YouTube images to identify common trends or features (unsurprisingly, cat videos were found to be popular). Now, a group of University of Pennsylvania researchers are looking to utilize the technique for biological science, using it to uncover new information about…